opendrift.readers.basereader.structured
=======================================

.. py:module:: opendrift.readers.basereader.structured


Attributes
----------

.. autoapisummary::

   opendrift.readers.basereader.structured.logger


Classes
-------

.. autoapisummary::

   opendrift.readers.basereader.structured.StructuredReader


Module Contents
---------------

.. py:data:: logger

.. py:class:: StructuredReader

   Bases: :py:obj:`opendrift.readers.basereader.variables.Variables`


   A structured reader. Data is gridded on a regular grid. Used by e.g.:
   :class:`opendrift.readers.reader_netCDF_CF_generic.Reader`.

   Attributes:

       projected: is `True` if :class:`.fakeproj.fakeproj` is used because of missing projection information. The data points are assumed to be approximately equidistant on the surface (i.e. in meters).

       clipped: pixels to to remove along boundary (e.g. in case of bad data).

   .. seealso::

       :py:mod:`opendrift.readers`


   .. py:attribute:: clipped
      :value: 0



   .. py:attribute:: x
      :value: None



   .. py:attribute:: y
      :value: None



   .. py:attribute:: interpolation
      :value: 'linearNDFast'



   .. py:attribute:: convolve
      :value: None



   .. py:attribute:: save_interpolator
      :value: None



   .. py:attribute:: interpolator_filename
      :value: None



   .. py:attribute:: __lonlat2xy_parallel__
      :value: None



   .. py:attribute:: __disable_parallel__
      :value: False



   .. py:attribute:: var_block_before


   .. py:attribute:: var_block_after


   .. py:method:: get_variables(variables, time=None, x=None, y=None, z=None)
      :abstractmethod:


      Obtain a _block_ of values of the requested variables at all positions
      (x, y, z) closest to given time. These will be stored in
      :class:`opendrift.readers.interpolation.structured.ReaderBlock` and
      accessed from there.

      Arguments:
          variables: list of variables.

          time: datetime or None, time at which data are requested.

          x, y: float or ndarrays; coordinates of requested points.

          z: float or ndarray; vertical position (in meters, positive up)

        Returns:
          Dictionary

          keywords: variables (string)
          values: 2D ndarray bounding x and y.



   .. py:method:: prepare(extent, start_time, end_time, max_speed)

      Prepare reader for given simulation coverage in time and space.



   .. py:method:: set_convolution_kernel(convolve)

      Set a convolution kernel or kernel size (of array of ones) used by `get_variables` on read variables.



   .. py:method:: __convolve_block__(env)

      Convolve arrays with a kernel, if reader.convolve is set



   .. py:method:: lon_range()


   .. py:method:: _get_variables_interpolated_(variables, profiles, profiles_depth, time, reader_x, reader_y, z)

      This method _must_ be implemented by every reader. Usually by
      subclassing one of the reader types (e.g.
      :class:`structured.StructuredReader`).

      Arguments are in _native projection_ of reader.

      .. seealso:

          * :meth:`get_variables_interpolated_xy`.
          * :meth:`get_variables_interpolated`.



   .. py:method:: __check_env_arrays__(env)

      For the StructuredReader the variables are checked before entered into
      the ReaderBlock interpolator. This methods makes the second check a
      no-op.

      .. seealso::

          :meth:`.variables.Variables.__check_env_arrays__`.



   .. py:method:: xy2lonlat(x, y)

      Calculate x,y in own projection from given lon,lat (scalars/arrays).
              



   .. py:method:: lonlat2xy(lon, lat)

      Calculate lon,lat from given x,y (scalars/arrays) in own projection.



   .. py:method:: pixel_size()


   .. py:method:: get_ocean_depth_area_volume(lonmin, lonmax, latmin, latmax)

      Get depth, area and volume of ocean basin within given coordinates



   .. py:method:: _coverage_unit_()


   .. py:method:: _bbox_(x, y)

      Find bounding box on grid containing points (x, y)



   .. py:method:: _make_projected_grid_(lon, lat, eq_eps=0.1)

      Make the projected grid in cases where `lon` and `lat` are present as
      2D variables, but not `x` and `y` and assert that it is approximately
      equidistant.

      Args:

          eq_eps: tolerance for equidistance checks.



   .. py:method:: __validate_projected_grid__(eq_eps=0.1)

      Validate that the projected grid is approximately equidistant.

      Args:

          eq_eps: tolerance for equidistance checks.

      Raises:

          AssertionError if not equidistant within `eq_eps`.



   .. py:method:: _slice_variable_(var, indxTime=None, indy=None, indx=None, indz=None, indrealization=None)

      Slice variable depending on number of dimensions available.

      Args:

          All arguments can be `slice` objects or index.

      Returns:

          `var` sliced using the slices or indexes necessary to use depending
          on number of dimensions available.

      Raises:

          Unsupported number of dimensions (outside 2..5) raises an exception.